Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{190696,
        author = {Harisankar T S and Jibin Johnson and Antony Francis and Anooja V.S and Latha Dinesh},
        title = {UNDERGROUND CABLE FAULT DETECTION USING IOT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {3920-3924},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190696},
        abstract = {Underground cable faults cause long outages and expensive, time consuming excavation and repairs in urban distribution networks. This project develops an IoT enabled fault detection and location system for medium voltage underground cables that combines edge sensing (voltage/current / impedance sampling and partial discharge indicators), distance estimation algorithms (time domain reflectometry / impedance based pre location) and real time cloud reporting. A compact sensor/injector node (ESP32/MCU + measurement front end) continuously monitors electrical parameters and uploads processed fault alerts and estimated distances to a cloud dashboard via MQTT. When the system detects an anomaly (e.g., sudden earth fault, large PD signature, open or short), it pre locates the fault to a segment length using TDR/impedance calculations and timestamps the event for crew dispatch. A proof-of-concept lab setup and field trial on a short-buried cable demonstrator validate detection sensitivity and location error (target ¡1% of cable length). The solution aims to reduce time to pinpoint, excavation scope, and outage duration through automated alarms, GPS tagged fault locations, and historical analytics that support predictive maintenance. This work demonstrates feasibility of low cost IoT augmentation for existing cable networks and outlines pathways to integrate AI-assisted PD classification and optical-fiber sensing for future scalability},
        keywords = {Underground cable fault, GPS, IOT ,Distribution network.},
        month = {January},
        }